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Title: Development of handprinting character recognition system using two stage shape and stroke classification.
Creator: Tse, Hing Wing., Florida Atlantic University, Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This thesis deals with the recognition of digitized handprinting characters. Digitized character images are thresholded, binarized and converted into 32 x 32 matrices. The binarized character matrices are preprocessed to remove noise and thin down to one pixel per linewidth. For dominant features, namely, (1) number of loops, (2) number of end-pixels, (3) number of 3-branch-pixels, and (4) number of 4-branch-pixels, are used as criteria to pre-classify characters into 14 groups. Characters...
Show moreThis thesis deals with the recognition of digitized handprinting characters. Digitized character images are thresholded, binarized and converted into 32 x 32 matrices. The binarized character matrices are preprocessed to remove noise and thin down to one pixel per linewidth. For dominant features, namely, (1) number of loops, (2) number of end-pixels, (3) number of 3-branch-pixels, and (4) number of 4-branch-pixels, are used as criteria to pre-classify characters into 14 groups. Characters belonging to larger groups are encoded into chain code and compiled into a data base. Recognition of characters belonging to larger groups is achieved by data base look-up and or decision tree tests if ambiguities occur in the data base entries. Recognition of characters belonging to the smaller groups is doned by decision tree tests.
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Date Issued: 1988
PURL: http://purl.flvc.org/fcla/dt/14486
Subject Headings: Optical character recognition devices, Pattern recognition systems
Format: Document (PDF)

Title: Automated biometrics of audio-visual multiple modals.
Creator: Huang, Lin, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Biometrics is the science and technology of measuring and analyzing biological data for authentication purposes. Its progress has brought in a large number of civilian and government applications. The candidate modalities used in biometrics include retinas, fingerprints, signatures, audio, faces, etc. There are two types of biometric system: single modal systems and multiple modal systems. Single modal systems perform person recognition based on a single biometric modality and are affected by...
Show moreBiometrics is the science and technology of measuring and analyzing biological data for authentication purposes. Its progress has brought in a large number of civilian and government applications. The candidate modalities used in biometrics include retinas, fingerprints, signatures, audio, faces, etc. There are two types of biometric system: single modal systems and multiple modal systems. Single modal systems perform person recognition based on a single biometric modality and are affected by problems like noisy sensor data, intra-class variations, distinctiveness and non-universality. Applying multiple modal systems that consolidate evidence from multiple biometric modalities can alleviate those problems of single modal ones. Integration of evidence obtained from multiple cues, also known as fusion, is a critical part in multiple modal systems, and it may be consolidated at several levels like feature fusion level, matching score fusion level and decision fusion level. Among biometric modalities, both audio and face modalities are easy to use and generally acceptable by users. Furthermore, the increasing availability and the low cost of audio and visual instruments make it feasible to apply such Audio-Visual (AV) systems for security applications. Therefore, this dissertation proposes an algorithm of face recognition. In addition, it has developed some novel algorithms of fusion in different levels for multiple modal biometrics, which have been tested by a virtual database and proved to be more reliable and robust than systems that rely on a single modality.
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Date Issued: 2010
PURL: http://purl.flvc.org/FAU/1927864
Subject Headings: Pattern recognition systems, Optical pattern recognition, Biometric identification, Identification, Automation, Automatic speech recognition
Format: Document (PDF)

Title: Peripheral Object Recognition in Naturalistic Scenes.
Creator: Schlangen, Derrick, Barenholtz, Elan, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description: Most of the human visual field falls in the periphery, and peripheral processing is important for normal visual functioning. Yet, little is known about peripheral object recognition in naturalistic scenes and factors that modulate this ability. We propose that a critical function of scene and object memory is in order to facilitate visual object recognition in the periphery. In the first experiment, participants identified objects in scenes across different levels of familiarity and...
Show moreMost of the human visual field falls in the periphery, and peripheral processing is important for normal visual functioning. Yet, little is known about peripheral object recognition in naturalistic scenes and factors that modulate this ability. We propose that a critical function of scene and object memory is in order to facilitate visual object recognition in the periphery. In the first experiment, participants identified objects in scenes across different levels of familiarity and contextual information within the scene. We found that familiarity with a scene resulted in a significant increase in the distance that objects were recognized. Furthermore, we found that a semantically consistent scene improved the distance that object recognition is possible, supporting the notion that contextual facilitation is possible in the periphery. In the second experiment, the preview duration of a scene was varied in order to examine how a scene representation is built and how memory of that scene and the objects within it contributes to object recognition in the periphery. We found that the closer participants fixated to the object in the preview, the farther on average they recognized that target object in the periphery. However, only a preview duration of the scenes for 5000 ms produced significantly farther peripheral object recognition compared to not previewing the scene. Overall, these experiments introduce a novel research paradigm for object recognition in naturalistic scenes, and demonstrates multiple factors that have systematic effects on peripheral object recognition.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004669, http://purl.flvc.org/fau/fd/FA00004669
Subject Headings: Context effects (Psychology), Human information processing, Optical pattern recognition, Pattern recognition systems, Recognition (Psychology), Visual perception
Format: Document (PDF)

Title: 2D/3D face recognition.
Creator: Guan, Xin., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This dissertation introduces our work on face recognition using a novel approach based on creating 3D face model from 2D face images. Together with the pose angle estimation and illumination compensation, this method can be used successfully to recognize 2D faces with 3D recognition algorithms. The results reported here were obtained partially with our own face image database, which had 2D and 3D face images of 50 subjects, with 9 different pose angles. It is shown that by applying even the...
Show moreThis dissertation introduces our work on face recognition using a novel approach based on creating 3D face model from 2D face images. Together with the pose angle estimation and illumination compensation, this method can be used successfully to recognize 2D faces with 3D recognition algorithms. The results reported here were obtained partially with our own face image database, which had 2D and 3D face images of 50 subjects, with 9 different pose angles. It is shown that by applying even the simple PCA algorithm, this new approach can yield successful recognition rates using 2D probing images and 3D gallery images. The insight gained from the 2D/3D face recognition study was also extended to the case of involving 2D probing and 2D gallery images, which offers a more flexible approach since it is much easier and practical to acquire 2D photos for recognition. To test the effectiveness of the proposed approach, the public AT&T face database, which had 2D only face photos of 40 subjects, with 10 different images each, was utilized in the experimental study. The results from this investigation show that with our approach, the 3D recognition algorithm can be successfully applied to 2D only images. The performance of the proposed approach was further compared with some of the existing face recognition techniques. Studies on imperfect conditions such as domain and pose/illumination variations were also carried out. Additionally, the performance of the algorithms on noisy photos was evaluated. Pros and cons of the proposed face recognition technique along with suggestions for future studies are also given in the dissertation.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342104
Subject Headings: Pattern recognition systems, Optical pattern recognition, Biometric identification, Face perception, Artificial intellingence
Format: Document (PDF)

Title: How the Spatial Organization of Objects Affects Perceptual Processing of a Scene.
Creator: Rashford, Stacey, Barenholtz, Elan, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description: How does spatial organization of objects affect the perceptual processing of a scene? Surprisingly, little research has explored this topic. A few studies have reported that, when simple, homogenous stimuli (e.g., dots), are presented in a regular formation, they are judged to be more numerous than when presented in a random configuration (Ginsburg, 1976; 1978). However, these results may not apply to real-world objects. In the current study, fewer objects were believed to be on organized...
Show moreHow does spatial organization of objects affect the perceptual processing of a scene? Surprisingly, little research has explored this topic. A few studies have reported that, when simple, homogenous stimuli (e.g., dots), are presented in a regular formation, they are judged to be more numerous than when presented in a random configuration (Ginsburg, 1976; 1978). However, these results may not apply to real-world objects. In the current study, fewer objects were believed to be on organized desks than their disorganized equivalents. Objects that are organized may be more likely to become integrated, due to classic Gestalt principles. Consequently, visual search may be more difficult. Such object integration may diminish saliency, making objects less apparent and more difficult to find. This could explain why, in the present study, objects on disorganized desks were found faster.
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Date Issued: 2015
PURL: http://purl.flvc.org/fau/fd/FA00004537, http://purl.flvc.org/fau/fd/FA00004537
Subject Headings: Image analysis, Optical pattern recognition, Pattern recognition systems, Phenomenological psychology, Visual perception
Format: Document (PDF)

Title: Self-relevant familiarity effects on object recognition: effects of context, location and object's size.
Creator: Daskagianni, Evangelie., Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description: Recent research in visual object recognition has shown that context can facilitate object recognition. This study assessed the effect of self-relevant familiarity of context in object recognition. Participants performed a task in which they had to recognize degraded objects shown under varying levels of contextual information. The level of degradation at which they could successfully recognize the target object was used as a measure of performance. There were five contextual conditions: (1)...
Show moreRecent research in visual object recognition has shown that context can facilitate object recognition. This study assessed the effect of self-relevant familiarity of context in object recognition. Participants performed a task in which they had to recognize degraded objects shown under varying levels of contextual information. The level of degradation at which they could successfully recognize the target object was used as a measure of performance. There were five contextual conditions: (1) no context, (2) context, (3) context and size, (4) context and location, (5) context, size and location. Within each contextual condition, we compared the performance of "Expert" participants who viewed objects in the context of their own house and "Novice" participants who viewed those particular settings for the first time. Ratings were performed to assess each object's consistency, frequency, position consistency, typicality and shape distinctiveness. Object's size was the only contextual info rmation that did not affect performance. Contextual information significantly reduced the amount of bottom-up visual information needed for object identification for both experts and novices. An interaction (Contextual Information x Level of Familiarity) was observed. Expert participants' performance improved significantly more than novice participants' performance by the presence of contextual information. Location information affected the performance of expert participants, only when objects that occupied stable positions were considered. Both expert and novice participants performed better with objects that rated high in typicality and shape distinctiveness. Object's consistency, frequency and position consistency did not seem to affect expert participants' performance but did affect novice participants' performance., A regression analysis model that included Level of Familiarity, Contextual Information Level, Shape and Typical performance. Our results are in accordance with the priming model of visual object recognition. We concluded that a self-relevant context has its own consistency rules and that it affects visual object recognition by narrowing down the number of expectations and the search space significantly more than a non-self-relevant context does. Keywords: visual object recognition, self-relevant familiarity, location, size, probability.
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Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3332183
Subject Headings: Optical pattern recognition, Context effects (Psychology), Visual perception, Categorization (Psychology), Recognition (Psychology), Whole and parts (Psycholog)
Format: Document (PDF)

Title: Design of analog building blocks useful for artificial neural networks.
Creator: Renavikar, Ajit Anand., Florida Atlantic University, Shankar, Ravi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Software simulations of a scaleable VLSI implementable architecture and algorithm for character recognition by a research group at Florida Atlantic University (FAU) have shown encouraging results. We address here hardware implementation issues pertinent to the classification phase of character recognition. Using the digit classification techniques developed at FAU as a foundation, we have designed and simulated general purpose building blocks useful for a possible implementation of a Digital ...
Show moreSoftware simulations of a scaleable VLSI implementable architecture and algorithm for character recognition by a research group at Florida Atlantic University (FAU) have shown encouraging results. We address here hardware implementation issues pertinent to the classification phase of character recognition. Using the digit classification techniques developed at FAU as a foundation, we have designed and simulated general purpose building blocks useful for a possible implementation of a Digital & Analog CMOS VLSI chip that is suitable for a variety of artificial neural network (ANN) architectures. HSPICE was used to perform circuit-level simulations of the building blocks. We present here the details of implementation of the recognition chip including the architecture, circuit design and the simulation results.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15328
Subject Headings: Neural networks (Computer science), Artificial intelligence, Optical character recognition devices, Pattern recognition systems
Format: Document (PDF)

Title: DIGITAL IMAGE PROCESSING APPLIED TO CHARACTER RECOGNITION.
Creator: BEGUN, RALPH MURRAY., Florida Atlantic University, Erdol, Nurgun
Abstract/Description: Surveys are made of both character recognition and image processing. The need to apply image processing techniques to character recognition is pointed out. The fields are then combined and tested in sample programs. Simulations are made of recognition systems with and without image preprocessing. Processing techniques applied utilize Walsh-Hadamard transforms and l ocal window operators. Results indicate that image prepro c ess i ng improves recognition rates when noise degrades input images....
Show moreSurveys are made of both character recognition and image processing. The need to apply image processing techniques to character recognition is pointed out. The fields are then combined and tested in sample programs. Simulations are made of recognition systems with and without image preprocessing. Processing techniques applied utilize Walsh-Hadamard transforms and l ocal window operators. Results indicate that image prepro c ess i ng improves recognition rates when noise degrades input images. A system architecture is proposed for a hardware based video speed image processor operating on local image windows. The possible implementation of this processor is outlined.
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Date Issued: 1982
PURL: http://purl.flvc.org/fcla/dt/14120
Subject Headings: Image processing--Digital techniques, Optical character recognition devices, Pattern recognition systems
Format: Document (PDF)

Title: A VLSI implementation of a hexagonal topology CCD image sensor.
Creator: Madabushi, Vasudhevan., Florida Atlantic University, Shankar, Ravi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In this thesis we report a VLSI design implementation of an application specific, full-frame architecture CCD image sensor for a handwritten Optical Character Recognition system. The design is targeted to the MOSIS 2mu, 2-poly/ 2-metal n-buried channel CCD/CMOS technology. The front side illuminated CCD image sensor uses a transparent polysilicon gate structure and is comprised of 84 (H) x 100 (V) pixels arranged in a hexagonal lattice structure. The sensor has unit pixel dimensions of 18...
Show moreIn this thesis we report a VLSI design implementation of an application specific, full-frame architecture CCD image sensor for a handwritten Optical Character Recognition system. The design is targeted to the MOSIS 2mu, 2-poly/ 2-metal n-buried channel CCD/CMOS technology. The front side illuminated CCD image sensor uses a transparent polysilicon gate structure and is comprised of 84 (H) x 100 (V) pixels arranged in a hexagonal lattice structure. The sensor has unit pixel dimensions of 18 lambda (H) x 16 lambda (V). A second layer of metal is used for shielding certain areas from incident light, and the effective pixel photosite area is 8 lambda x 8 lambda. The imaging pixels use a 3-phase structure (with an innovative addressing scheme for the hexagonal lattice) for image sensing and horizontal charge shift. Columns of charge are shifted into the vertical 2-phase CCD shift registers, which shift the charge out serially at high speed. The chip has been laid out on the 'tinychip' (2250 mu m x 2220 (mu m) pad frame and fabrication through MOSIS is planned next.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/15123
Subject Headings: Integrated circuits--Very large scale integration, Optical character recognition devices, Pattern recognition systems, Imaging systems
Format: Document (PDF)

Title: A VLSI implementable handwritten digit recognition system using artificial neural networks.
Creator: Agba, Lawrence C., Florida Atlantic University, Shankar, Ravi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: A VLSI implementable feature extraction scheme, and two VLSI implementable algorithms for feature classification that should lead to a practical handwritten digit recognition system are proposed. The feature extraction algorithm exploits the concept of holon dynamics. Holons can be regarded as a group of cooperative processors with self-organizing property. Two types of artificial neural network-based classifiers have been evolved to classify these features. The United States Post Office...
Show moreA VLSI implementable feature extraction scheme, and two VLSI implementable algorithms for feature classification that should lead to a practical handwritten digit recognition system are proposed. The feature extraction algorithm exploits the concept of holon dynamics. Holons can be regarded as a group of cooperative processors with self-organizing property. Two types of artificial neural network-based classifiers have been evolved to classify these features. The United States Post Office handwritten digit database was used to train and test these networks. The first type of classifier system used limited interconnect multi-layer perceptron (LIMP) modules in a hierarchical configuration. Each classifier in this system was independently trained and designated to recognize a particular digit. A maximum of sixty-one digits were used to train and 464 digits which included the training set were used to test the classifiers. A cumulative performance of 93.75% (correctly recognized digits) was recorded. The second classifier system consists of a cluster of small multi-layer perceptron (CLUMP) networks. Each cell in this system was independently trained to trace the boundary between two or more digits in the recognition plane. A combination of these cells distinguish a digit from the rest. This system was trained with 1796 digits and tested on 1918 different set of digits. On the training set a performance of 95.55% was recorded while 79.35% resulted from the test data. These results, which are expected to further improve, are superior to those obtained by other researchers on the same database. This technique of digit recognition is general enough for application in the development of a universal alphanumeric recognition system. A hybrid VLSI system consisting of both analog and digital circuitry, and utilizing both Bi-CMOS and switched capacitor technologies has been designed. The design is intended for implementation with the current MOSIS 2 $\mu$m, double poly, double metal, and p-well CMOS technology. The integrated circuit is such that both classifier systems can be realized using the same chip.
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Date Issued: 1990
PURL: http://purl.flvc.org/fcla/dt/12260
Subject Headings: Optical character recognition devices--Computer simulation, Pattern recognition systems--Computer simulation
Format: Document (PDF)

Title: Feature extraction implementation for handwritten numeral recognition.
Creator: Banuru, Prashanth K., Florida Atlantic University, Shankar, Ravi
Abstract/Description: Feature extraction for handwritten character recognition has always been a challenging problem for investigators in the field. The problem gets worse due to large variations present for each type of input character. Our algorithm computes directional features for alphanumeric input mapped on to a hexagonal lattice. The algorithm implements size and scale invariance that is a requirement for achieving a reasonably good recognition rate. Functional performance has been verified for an hexagonal...
Show moreFeature extraction for handwritten character recognition has always been a challenging problem for investigators in the field. The problem gets worse due to large variations present for each type of input character. Our algorithm computes directional features for alphanumeric input mapped on to a hexagonal lattice. The algorithm implements size and scale invariance that is a requirement for achieving a reasonably good recognition rate. Functional performance has been verified for an hexagonal lattice mapped input on the data obtained from the US postal service handwritten character database. In this thesis, we implemented the algorithm in a Xilinx FPGA (XC4xxx series).
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Date Issued: 1994
PURL: http://purl.flvc.org/fcla/dt/15103
Subject Headings: Algorithms, Pattern recognition systems--Computer simulation, Optical character recognition devices--Computer simulation
Format: Document (PDF)

Title: Handwritten digit recognition using neural network integrated chips.
Creator: Bidari, Ravindra Chandrashekar., Florida Atlantic University, Shankar, Ravi
Abstract/Description: Development of a handwritten digit recognition system for real time applications is a feasible goal today due to the many advances pertinent to VLSI. In this research we address the issue of mapping our neural net classification algorithm to Intel's commercially available general purpose Neural Network Chip, 80170NX (ETANN). Most of the proposed techniques used for character recognition have been validated by our research group using various software and hardware simulation methods. The...
Show moreDevelopment of a handwritten digit recognition system for real time applications is a feasible goal today due to the many advances pertinent to VLSI. In this research we address the issue of mapping our neural net classification algorithm to Intel's commercially available general purpose Neural Network Chip, 80170NX (ETANN). Most of the proposed techniques used for character recognition have been validated by our research group using various software and hardware simulation methods. The objective of this thesis was to develop a practical hardware system to perform the final step of classification of handwritten digits in an Optical Character Recognition (OCR) system. Such a hardware implementation would increase the classification speed and also would permit testing in a real life application environment. An efficient mapping scheme was evolved to map the modules of a limited interconnect classification algorithm, CLUMP, to a minimum number of ETANN chips. The hardware modules to interface the ETANN chips to MC68000 education board have been developed and tested. The proposed system is estimated to process the features input in 336 $\mu$s, for our specific implementation, with 12 clock phases and 3 ETANN chips.
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Date Issued: 1992
PURL: http://purl.flvc.org/fcla/dt/14838
Subject Headings: Optical character recognition devices--Computer simulation, Pattern recognition systems--Computer simulation
Format: Document (PDF)

Title: A Study in Implementing Autonomous Video Surveillance Systems Based on Optical Flow Concept.
Creator: Fonseca, Alvaro A., Zhuang, Hanqi, Marques, Oge, Florida Atlantic University
Abstract/Description: Autonomous video surveillance systems are usually built with several functional blocks such as motion detection, foreground and background separation, object tracking, depth estimation, feature extraction and behavioral analysis of tracked objects. Each of those blocks is usually designed with different techniques and algorithms, which may need significant computational and hardware resources. In this thesis we present a surveillance system based on an optical flow concept, as a main unit on...
Show moreAutonomous video surveillance systems are usually built with several functional blocks such as motion detection, foreground and background separation, object tracking, depth estimation, feature extraction and behavioral analysis of tracked objects. Each of those blocks is usually designed with different techniques and algorithms, which may need significant computational and hardware resources. In this thesis we present a surveillance system based on an optical flow concept, as a main unit on which other functional blocks depend. Optical flow limitations, capabilities and possible problem solutions are discussed in this thesis. Moreover, performance evaluation of various methods in handling occlusions, rigid and non-rigid object classification, segmentation and tracking is provided for a variety of video sequences under different ambient conditions. Finally, processing time is measured with software that shows an optical flow hardware block can improve system performance and increase scalability while reducing the processing time by more than fifty percent.
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Date Issued: 2007
PURL: http://purl.flvc.org/fau/fd/FA00012516
Subject Headings: Electronic surveillance, Optical pattern recognition, Computer vision, Optical flow--Image analysis
Format: Document (PDF)

Title: A hybrid color‐based foreground object detection method for automated marine surveillance.
Creator: Furht, Borko, Kalva, Hari, Marques, Oge, Culibrk, Dubravko, Socek, Daniel
Date Issued: 2005
PURL: http://purl.flvc.org/fcla/dt/358420
Subject Headings: Computer vision., Automatic tracking., Digital video., Image processing., Optical pattern recognition.
Format: Document (PDF)

Title: A systematic evaluation of object detection and recognition approaches with context capabilities.
Creator: Giusti Urbina, Rafael J., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Contemporary computer vision solutions to the problem of object detection aim at incorporating contextual information into the process. This thesis proposes a systematic evaluation of the usefulness of incorporating knowledge about the geometric context of a scene into a baseline object detection algorithm based on local features. This research extends publicly available MATLABRª implementations of leading algorithms in the field and integrates them in a coherent and extensible way....
Show moreContemporary computer vision solutions to the problem of object detection aim at incorporating contextual information into the process. This thesis proposes a systematic evaluation of the usefulness of incorporating knowledge about the geometric context of a scene into a baseline object detection algorithm based on local features. This research extends publicly available MATLABRª implementations of leading algorithms in the field and integrates them in a coherent and extensible way. Experiments are presented to compare the performance and accuracy between baseline and context-based detectors, using images from the recently published SUN09 dataset. Experimental results demonstrate that adding contextual information about the geometry of the scene improves the detector performance over the baseline case in 50% of the tested cases.
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Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3183127
Subject Headings: Imaging systems, Mathematical models, Cognitive science, Optical pattern recognition, Computer vision, Logistic regression analysis
Format: Document (PDF)

Title: Informational Aspects of Audiovisual Identity Matching.
Creator: Mavica, Lauren Wood, Barenholtz, Elan, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description: In this study, we investigated what informational aspects of faces could account for the ability to match an individual’s face to their voice, using only static images. In each of the first six experiments, we simultaneously presented one voice recording along with two manipulated images of faces (e.g. top half of the face, bottom half of the face, etc.), a target face and distractor face. The participant’s task was to choose which of the images they thought belonged to the same individual as...
Show moreIn this study, we investigated what informational aspects of faces could account for the ability to match an individual’s face to their voice, using only static images. In each of the first six experiments, we simultaneously presented one voice recording along with two manipulated images of faces (e.g. top half of the face, bottom half of the face, etc.), a target face and distractor face. The participant’s task was to choose which of the images they thought belonged to the same individual as the voice recording. The voices remained un-manipulated. In Experiment 7 we used eye tracking in order to determine which informational aspects of the model’s faces people are fixating while performing the matching task, as compared to where they fixate when there are no immediate task demands. We presented a voice recording followed by two static images, a target and distractor face. The participant’s task was to choose which of the images they thought belonged to the same individual as the voice recording, while we tracked their total fixation duration. In the no-task, passive viewing condition, we presented a male’s voice recording followed sequentially by two static images of female models, or vice versa, counterbalanced across participants. Participant’s results revealed significantly better than chance performance in the matching task when the images presented were the bottom half of the face, the top half of the face, the images inverted upside down, when presented with a low pass filtered image of the face, and when the inner face was completely blurred out. In Experiment 7 we found that when completing the matching task, the time spent looking at the outer area of the face increased, as compared to when the images and voice recordings were passively viewed. When the images were passively viewed, the time spend looking at the inner area of the face increased. We concluded that the inner facial features (i.e. eyes, nose, and mouth) are not necessary informational aspects of the face which allow for the matching ability. The ability likely relies on global features such as the face shape and size.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004688, http://purl.flvc.org/fau/fd/FA00004688
Subject Headings: Biometric identification, Eye -- Movements, Nonverbal communication, Optical pattern recognition, Sociolinguistics, isual perception
Format: Document (PDF)

Title: An Intelligent Method For Violence Detection in Live Video Feeds.
Creator: Eneim, Maryam, Marques, Oge, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In the past few years, violence detection has become an increasingly rele- vant topic in computer vision with many proposed solutions by researchers. This thesis proposes a solution called Criminal Aggression Recognition Engine (CARE), an OpenCV based Java implementation of a violence detection system that can be trained with video datasets to classify action in a live feed as non-violent or violent. The algorithm extends existing work on fast ght detection by implementing violence detection...
Show moreIn the past few years, violence detection has become an increasingly rele- vant topic in computer vision with many proposed solutions by researchers. This thesis proposes a solution called Criminal Aggression Recognition Engine (CARE), an OpenCV based Java implementation of a violence detection system that can be trained with video datasets to classify action in a live feed as non-violent or violent. The algorithm extends existing work on fast ght detection by implementing violence detection of live video, in addition to prerecorded video. The results for violence detection in prerecorded videos are comparable to other popular detection systems and the results for live video are also very encouraging, making the work proposed in this thesis a solid foundation for improved live violence detection systems.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004775, http://purl.flvc.org/fau/fd/FA00004775
Subject Headings: Multimedia systems., Image analysis., Computer vision., Visual communication--Social aspects., Social problems--21st century., Pattern recognition systems., Optical pattern recognition.
Format: Document (PDF)

Title: Eye Fixations of the Face Are Modulated by Perception of a Bidirectional Social Interaction.
Creator: Kleiman, Michael J., Barenholtz, Elan, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description: Eye fixations of the face are normally directed towards either the eyes or the mouth, however the proportions of gaze to either of these regions are dependent on context. Previous studies of gaze behavior demonstrate a tendency to stare into a target’s eyes, however no studies investigate the differences between when participants believe they are engaging in a live interaction compared to knowingly watching a pre-recorded video, a distinction that may contribute to studies of memory encoding....
Show moreEye fixations of the face are normally directed towards either the eyes or the mouth, however the proportions of gaze to either of these regions are dependent on context. Previous studies of gaze behavior demonstrate a tendency to stare into a target’s eyes, however no studies investigate the differences between when participants believe they are engaging in a live interaction compared to knowingly watching a pre-recorded video, a distinction that may contribute to studies of memory encoding. This study examined differences in fixation behavior for when participants falsely believed they were engaging in a real-time interaction over the internet (“Real-time stimulus”) compared to when they knew they were watching a pre-recorded video (“Pre-recorded stimulus”). Results indicated that participants fixated significantly longer towards the eyes for the pre-recorded stimulus than for the real-time stimulus, suggesting that previous studies which utilize pre-recorded videos may lack ecological validity.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004701, http://purl.flvc.org/fau/fd/FA00004701
Subject Headings: Eye -- Movements, Eye tracking, Gaze -- Psychological aspects, Nonverbal communication, Optical pattern recognition, Perceptual motor processes, Visual perception
Format: Document (PDF)

Title: Optical 2D Positional Estimation for a Biomimetic Station-Keeping Autonomous Underwater Vehicle.
Creator: Nunes, Christopher, Dhanak, Manhar R., Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: Underwater vehicles often use acoustics or dead reckoning for global positioning, which is impractical for low cost, high proximity applications. An optical based positional feedback system for a wave tank operated biomimetic station-keeping vehicle was made using an extended Kalman filter and a model of a nearby light source. After physical light model verification, the filter estimated surge, sway, and heading with 6 irradiance sensors and a low cost inertial measurement unit (~$15)....
Show moreUnderwater vehicles often use acoustics or dead reckoning for global positioning, which is impractical for low cost, high proximity applications. An optical based positional feedback system for a wave tank operated biomimetic station-keeping vehicle was made using an extended Kalman filter and a model of a nearby light source. After physical light model verification, the filter estimated surge, sway, and heading with 6 irradiance sensors and a low cost inertial measurement unit (~$15). Physical testing with video feedback suggests an average error of ~2cm in surge and sway, and ~3deg in yaw, over a 1200 cm2 operational area. This is 2-3 times better, and more consistent, than adaptations of prior art tested alongside the extended Kalman filter feedback system. The physical performance of the biomimetic platform was also tested. It has a repeatable forward velocity response with a max of 0.3 m/s and fair stability in surface testing conditions.
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Date Issued: 2015
PURL: http://purl.flvc.org/fau/fd/FA00004528, http://purl.flvc.org/fau/fd/FA00004528
Subject Headings: Biometric identification, Feedback control systems, Oceanographic submersibles -- Design and construction, Optical pattern recognition, Remote submersibles -- Design and construction
Format: Document (PDF)

Title: Optical Characterization ofPort Everglades Focusing on Underwater Visibility.
Creator: Whipple, Dustin E., Frisk, George V., Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: The development of an unmanned underwater vehicle at Florida Atlantic University with onboard optical sensors has prompted the temporal and spatial optical characterization of Port Everglades, with in-situ measurements of the turbidity, conductivity, and temperature. Water samples were collected for laboratory analysis where attenuation and absorption were measured with a bench top spectrometer. All of the measurements showed a high degree of variability within the port on a temporal and...
Show moreThe development of an unmanned underwater vehicle at Florida Atlantic University with onboard optical sensors has prompted the temporal and spatial optical characterization of Port Everglades, with in-situ measurements of the turbidity, conductivity, and temperature. Water samples were collected for laboratory analysis where attenuation and absorption were measured with a bench top spectrometer. All of the measurements showed a high degree of variability within the port on a temporal and spatial basis. Correlations were researched between the measured properties as well as tide and current. Temporal variations showed a high correlation to tidal height but no relation was found between turbidity and current, or salinity. Spatial variations were primarily determined by proximity to the port inlet. Proportionality constants were discovered to relate turbidity to scattering and absorption coefficients. These constants along with future turbidity measurements will allow the optimization of any underwater camera system working within these waters.
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Date Issued: 2007
PURL: http://purl.flvc.org/fau/fd/FA00012569
Subject Headings: Oceanographic submersibles--Mathematical models, Image processing--Digital techniques, Optical pattern recognition, Port Everglades (Fort Lauderdale, Fla)
Format: Document (PDF)

FAU Theses and Dissertations (24)	+ -
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